Object identification in dynamic environment using sensor fusion

Multisensor data fusion is highly applicable in robotics applications because the relationships among objects and events changes due to the change in orientation of robot, snag in sensory information, sensor range and environmental conditions etc. High level and low level image processing in machine vision are widely involved to investigate object identification in complex application. Due to the limitations of vision technology still it is difficult to identify the objects in certain environments. A new technique of object identification using sonar sensor fusion has been proposed. This paper explains the computational account of the data fusion using Bayesian and neural network to recognize the shape of object in the dynamic environment.